We will analyze CT colonography (virtual colonoscopy) data using computer-assisted diagnosis methods. These methods attempt to identify and characterize colonic polyps automatically, thereby improving physician accuracy and efficiency. We will compare the results of the computer analyses with the ground truth data (conventional colonoscopy, pathologic analysis).[unreadable] [unreadable] We made a number of advances over the past year, including advances in colon and polyp segmentation, feature extraction methods, false positive reduction and classifier optimization. We just developed an innovative technique to use the tenia coli (longitudinal muscle bands) as a guide for orienting the supine and prone virtual colonoscopies. This technique has broad implications for research and clinical image interpretation. We improved detection of smaller polyps by as much as 20%. We also licensed our CAD software to a company that is in the process of commercializing the software. We anticipate our research being able to help patients directly in the near future when this commercialization is successful and the technology moves from the "bench-to-the-bedside".